By Bioforsk SEALINK Team

Transkript

1 By Bioforsk SEALINK Team Annelene Pengerud Csilla Farkas Hans Olav Eggestad Johannes Deelstra Per Stålnacke SWAT Workshop 20 May, 2009 Bioforsk, Ås, Norway

2 In general To investigate the retention and distribution of water and inorganic N compounds in the aquatic and terrestrial environment To improve our understanding on surface, subsurface and in stream processes, characteristic for the Skuterud catchment with respect to various measures Performing scenario analyses to investigate the combined effect of different land use and climate change scenarios on runoff, erosion and in stream water quantity and quality Within the SEALINK Project Providing appropriate INCA parameter set for agricultural lands in Southern Norway for simulating surface, subsurface and in stream water, N and P transport, using the advantage of a well-studied catchment (further used as initial parameter set for arable lands of the Vansjø catchment) Performing scenario analyses to investigate the effect of various land use change scenarios on in stream water quantity and quality

3 Aquatic Environments Research Centre, Dep. of Geography, Univ. of Reading INCA and EURO-Limacs European Projects INCA-N model (flow, nitrate and ammonium) Brazil, Denmark, England, Finland, France, Netherlands, Norway, Spain, Sweden, Wales INCA-SED (sediment transport and erosion) INCA-P INCA-C Denmark, England, Finland, Norway England, Finland England, Finland Other version for heavy metal transport etc. Romania

4 INCA-N model: process-based semi-distributed dynamic model of the N-cycle in the plant/soil and in-stream systems INCA-N simulates at a daily time-step water flow and storage nitrogen export from different land-use types within a river system in-stream nitrate and ammonium concentrations Catchment hydrology: direct runoff soil zone groundwater zone N processes: N cycle in terrestrial part inorganic N losses from land to river nitrification and denitrification in river

5 Driving variables in daily time-step soil moisture deficit hydraulically effective rainfall air temperature actual precipitation INCA - N Average annual riverine load of inorganic nitrogen N-balance elements for different land use types Model parameters sub-catchment reach in-stream land-phase general parameters Initial conditions Nitrogen transformation rates Hydrogeological parameters etc. Daily estimates of water discharge and NO 3 and NH 4 concentrations in river water

6 Cell Model Land component Evaporation Precipitation Surface runoff to stream Hydraulically effective rainfall Soil surface Transport to stream = (1 b) * q sz Soil zone Percolation = b * q sz Transport to stream = q gz Groundwater zone In-stream cell

7 x 1, x 2 output flows of the two zones (m 3 / s) T 1, T 2 time zone constants (1/s) U 1 input hydraulically effective rainfall (m) U 8 base flow index t- time (s)

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9 x3 and x4 - daily NO3-N concentrations (mg/l) in the soil zone and groundwater zone, respectively x5 and x6 - daily NH4-N concentrations (mg/l) in the soil zone and groundwater zone, respectively U8 - baseflow index C3, C6, C1, C2, C10, C7 and C8 - rate coefficients (per day) for respectively, plant uptake of nitrate, ammonia nitrification, nitrate denitrification, nitrate fixation, plant uptake of ammonia, ammonia mineralisation and ammonia immobilisation U3 and U4 - daily nitrate-nitrogen and ammonium-nitrogen loads entering the soil zone and constitute the additional dry and wet deposition and agricultural inputs (e.g. fertiliser addition)

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11 River flow model I inflow (m 3 /s) Q - outflow (m 3 /s) S - Storage (m 3 ) t time (s) T travel time parameter (s) L reach length (m) v mean flow velocity (m/s) Equations for NO3-N and NH4-N in river reaches U 9 - upstream flow (m3/s) U 10 - upstream NO3-N (mg/l) U 11 - upstream NH4-N (mg/l) T 3 - reach time constant (or residence time) x 7 - estimated downstream flow rate (m3/s) x 8 and x 9 - the downstream (i.e. reach output) conc. of nitrate and ammonia, respectively C 17 and C 18 - temperature-dependent rate parameters for denitrification and nitrification, respectively V 3 and V 4 equivalent water volumes in soil and ground water zones (m3)

12 Total area km 2 Low base flow and high flashiness index Subsurface drainage system Productive forest Winter processes

13 Calibration period: 1 January, December, 1999 To set up the parameters for all the land use types, except the wetland Validation period: 1 January, December, 2007 Setting up wetland parameters Land use types: Forest (31%) Grass (2%) Arable, No Autumn Tillage (18%) Arable, Autumn Tillage (41%) Wetland (0% between ; to be parameterised for the period of ) Urban (8%) Catchment structure No sub-catchments, one reach No effluent No abstraction

14 1. Catchment and reach information Catchment area, reach length 2. Data on fertiliser application NO3 fertilisation input files 3. Crop data Multiple growth period input files 4. Soil data From reference soil profiles, belonging to the agricultural area Soils of the forest area were represented by a chosen reference soil profile from an arable land Setting up parameters (soil water deficit maximum; total/available water)

15 1. Driving variables HBV model run output, provided by NVE Soil moisture deficit; effective rainfall; air temperature; precipitation 2. Reference data Discharge measurements (daily data) Nitrate concentration data (composite sampling; approx. every 14 days)

16 1. Flow R 2 and N-S has to be comparable with those, obtained from the HBV runs Peculiarities of a small catchment, with high agricultural impact and productive forest have to be considered Subsurface drainage system effect has to be considered 2. Nitrate concentration Composite sampling and model outputs comparability Efforts to re-calculate the simulated nitrate concentrations

17 1. Parameterisation Available data from the Skuterud catchment and reach Literature review Expert assumptions 2. Calibration procedure Stepwise calibration approach (flow; flow&nitrate) flow flow&nitrate Incorporation of sensitivity analyses results 3. Validation procedure 4. Scenario analyses

18 1. Main hydrological parameters, against which the model appeared to be very sensitive Flow parameters a and b (from the discharge velocity relationship) Base flow index Soil moisture deficit maximum Soil reactive zone time constant Ratio of total to available water in soil

19 Velocity v (m s -1 ) Velocity v (m s -1 ) The relationship: v aq b Manningen: Q s A R s n Q s - Stream discharge (m 3 ) A - Wetted cross section (m 2 ) P - Wetted perimeter (m) R - Hydraulic radius = A/P (m) S - Slope of stream (m/m) n - Roughness parameter, varying between n = y = 1.163x R² = Discharge Q (m 3 ) 1.6 n = Skuterud_real Discharge Q (m 3 )

20 a=1.163; b=0.253 a=0.042; b= sim. - obs.

21 Velocity (v, m s -1 ) 2.0 v = a * Q ^b n(0.025)_real n(0.045)_real n(0.075)_real n(0.025)_calib n(0.045)_calib n(0.075)_calib Discharge (Q, m 3 )

22 - sim. - obs.

23 Simulated: app. 31 kg N /ha /year for Measured: 39 kg N/ ha /year for

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25 Flow dynamics often failed in summer periods Proportion between N-balance elements answered our expectations, but the NO 3 dynamic was not good Contribution of drain tiles to flow pathways could not be properly described Ratio between the in-stream and in-land processes? catchment size Winter conditions Improved driving variables from new precipitation data NVE How to parameterise land use parameters further? Differentiation?

26 Thank you for attention!

27 Base flow index: 0.19 Soil moisture deficit maximum: forest: 320; grass: 300; no till: 280; till: 250; urban: 100 Ratio of total to available water in soil Soil profile Soil layer Water content at saturation Plant-available water Ratio of total to plant-available water (-) Average ratio Location or land use (SKU 001) (SKU 002) (SKU 003) C2 (Pestrisk) (cm) (v%) (v%) (-) (-) Cereal Cereal Cereal BUT under forest also Direct drilling, farm

28 Parameter name Specific heat capacity due to freeze/thought Maximum temperature difference Degree day factor for snowmelt Thermal conductivity of soil Thermal properties Forest Ref Grass Ref Arable Ref Urban Ref. min max initial min 2 2, 4 2 2, 4 2 2,4 2 2,4 max initial min max initial min min Initial Rankinen et al., 2004a 2. Rankinen et al., 2004b 3. Ranzini et al., Savijoki input file 5. Tamar input file

29 Soil water denitrification rate Nitrogen fixation rate Plant uptake rate nitrate Maximum nitrogen uptake rate Ammonium nitrification rate Ammonium mineralisation rate Ammonium immobilisation rate Plant uptake rate / ammonium Forest Ref. code Grass Ref. code Arable Ref. code Urban m day -1 min , , ,5 0 4 kg ha -1 day -1 max ,3, ,6 initial min ,3 0 1,3 0 1,3 0 2,6 max , ,6 initial m day -1 min kg ha -1 max 0.1(3.5) 5(3) , ,6 initial day -1 min ,6 min 70 4, Initial Ref. code m day -1 min ,5,6 kg ha -1 day -1 max 0.8 5, , initial min ,5,6 max , initial m day -1 min max ,6 initial m day -1 min min 0.12(4.5) 3(6) ,6 Initial Granlund et al., 2004; 2. Manuscript_1; 3. Savijoki input file 4. Wade et tal., 2002; 5. Whitehead et al., 1998; 6. Tamar input file; 7. SOILN_NO

30 starting "0" param. File Skuterud flow a Skuterud flow b Skuterud base flow index Skuterud groundwater residence time Forest soil reactive zone time constant NoAutumT soil reactive zone time constant AutumT soil reactive zone time constant Reach Reach Catchment Catchment Land Use Land Use Land Use R2 R2 K-S_ _Hydr K-S_ _H&N Using calculated a, b as initial; changing base flow flow nitrate Fixed flow parameters "a" and "b" Fixed flow parameters "a" and "b" and fixed base flow index

31 Selected models - Eutrophication Hydrology models Because of the importance of process and models selected due to their difference in complexity: SCS HBV Water quality models Because of the varying need of high resolution in hydrology environment CE-QUAL-W2 Catchment models Because of the importance of diffuse and point sources and the models ability to perform scenario calculations TRK SWAT INCA Source apportionment and scenario tools Because of the importance of presentation and user friendly tests of scenarios of change WATSHMAN

32 Models comparison Models SCS HBV CE- QUAL- W2 Modest data requirements TRK SWAT INCA WATSHMAN Y Y N Y N Y Y High time resolution N Y Y Y Y Y Y High spatial resolution Processbased conceptual model Calibration data required Y Y Y Y Y Y Y N Y Y Y Y Y N N Y Y Y Y Y N Scenario possibilities N Y Y Y Y Y Y Complete catchment model N N N Y Y Y Y

33 Models comparison - continue Models SCS HBV CE- QUAL- W2 Distributed Y Y (semi) Y (fully) TRK SWAT INCA WATSHMAN Y (semi) Y (semi) Y (semi +) Time consuming N Y Y Y Y Y N Single interface N Y Y N Y Y Y Exchangeable submodels Applied for national assessments Applied in Northern Europe N Y - Y N* - Y - Y - Y - - N Y Y Y Y Y Y Y Non-Expert user Y N N N N N Y Freeware Y Y Y Y Y Y Y Y (semi) * some process submodels can be chosen in a scrollist and some can be exchanged - have not been verified